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To cope with this challenge, an adaptive pilot intent prediction\u2013based control algorithm is proposed to achieve compliant motion coordination. A novel surface electromyography signal processing method providing definite physical meaning and high computational efficiency is derived. The state space model of human musculoskeletal system is developed with the input of the processed surface electromyography. Adaptive parameter estimation is employed to cope with the emerging dynamics. It integrates the advantages of surface electromyography signals which imply muscle contraction in advance and force signals with high stability. Based on the coupled human\u2013exoskeleton system dynamics, transparent control of a human\u2013exoskeleton system is realized. Experimental results show that the computational efficiency of the proposed surface electromyography processing method is 129% higher than the energy kernel method, and the maximum interactive force is reduced about 15 N compared with impedance control.<\/jats:p>","DOI":"10.1177\/0959651820945814","type":"journal-article","created":{"date-parts":[[2020,8,25]],"date-time":"2020-08-25T05:03:58Z","timestamp":1598331838000},"page":"180-189","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Adaptive motion intent understanding\u2013based control of human\u2013exoskeleton system"],"prefix":"10.1177","volume":"235","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7350-6702","authenticated-orcid":false,"given":"JianTao","family":"Yang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Mechanical System and Vibration, Institute of Robotics, Shanghai Jiao Tong University, Shanghai, 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